erinys_distillDistills a stored observation into a higher abstraction level by observation ID, helping AI agents convert detailed memories into concise, reusable knowledge.
Distill observation to higher abstraction level.
| Name | Required | Description | Default |
|---|---|---|---|
| level | No | abstract | |
| observation_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.6.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden, yet it says nothing about whether distilling mutates the original observation, creates a new record, is reversible, or requires the observation to be in a particular state. Only one short sentence of pure intent is offered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single short sentence with no wasted words, but the brevity here reflects under-specification rather than disciplined editing; there is no front-loaded usage or scope information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists so return values need not be described, but for an unannotated two-parameter mutation-like tool in a large sibling family, the definition omits the essentials: what distillation produces, how level values behave, and what happens to the source observation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain both parameters, but it only gestures at them: "observation" loosely maps to observation_id and "higher abstraction level" to level without naming valid values (the default "abstract" is not mentioned or enumerated). No compensating detail is supplied.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a verb ("distill") and a resource ("observation") plus a direction ("higher abstraction level"), so the general intent is inferable. But "distill" and "abstraction level" are never defined, and nothing distinguishes this from abstractions produced by siblings such as erinys_dream or erinys_session_summary.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no statement of when to distill versus recall, summarize, dream, or supersede, and no prerequisites or exclusions. The agent must guess from the sibling list alone which tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.